Critical Care

Sepsis

Latest AI and machine learning research in sepsis for healthcare professionals.

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Critical-Care Subcategories: Sepsis
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High-Yield Preparation of American Oyster Defensin (AOD) via a Small and Acidic Fusion Tag and Its Functional Characterization.

The marine peptide, American oyster defensin (AOD), is derived from and exhibits a potent bacterici...

COVID-19 infection segmentation using hybrid deep learning and image processing techniques.

The coronavirus disease 2019 (COVID-19) epidemic has become a worldwide problem that continues to af...

Association between lactate metabolism‑related molecules and venous thromboembolism: A study based on bioinformatics and an model.

Venous thromboembolism (VTE) is characterized by a high recurrence rate and adverse consequences, in...

Unexpectedly Prolonged Serotonin Syndrome and Fatal Complications Following a Massive Overdose of Paroxetine Controlled-Release.

Symptoms caused by a selective serotonin reuptake inhibitor (SSRI) overdose are often mild and can b...

Perspective: Limiting Antimicrobial Resistance with Artificial Intelligence/Machine Learning.

The author traces his experience with the application of computers in clinical microbiology over the...

Fungal and bacterial gut microbiota differ between colonization and infection.

The bacterial microbiota is well-recognized for its role in colonization and infection, while fung...

Optimizing artificial intelligence in sepsis management: Opportunities in the present and looking closely to the future.

Sepsis remains a major challenge internationally for healthcare systems. Its incidence is rising due...

Effective Preventative Measures are Essential to Lower Disease Burden From Dengue and COVID-19 Co-infection in Bangladesh.

Bangladesh is widely recognized as one of the dengue prone nations, and empirical evidence has consi...

The application of artificial intelligence in the management of sepsis.

Sepsis is a complex and heterogeneous syndrome that remains a serious challenge to healthcare worldw...

Construct validation of machine learning for accurately predicting the risk of postoperative surgical site infection following spine surgery.

BACKGROUND: This study aimed to evaluate the risk factors for machine learning (ML) algorithms in pr...

FIAMol-AB: A feature fusion and attention-based deep learning method for enhanced antibiotic discovery.

Antibiotic resistance continues to be a growing concern for global health, accentuating the need for...

Masking of an intravenous preparation of ceftriaxone for use in clinical trials: A technical report.

BACKGROUND: Intravenous antibiotics are often evaluated in clinical trials in hospitalised patients ...

Mussel-Inspired Calcium Alginate/Polyacrylamide Dual Network Hydrogel: A Physical Barrier to Prevent Postoperative Re-Adhesion.

Intrauterine adhesions (IUA) has become one of the main causes of female infertility. How to effecti...

Plant leaf infected spot segmentation using robust encoder-decoder cascaded deep learning model.

Leaf infection detection and diagnosis at an earlier stage can improve agricultural output and reduc...

Antibiotics, Sedatives, and Catecholamines Further Compromise Sepsis-Induced Immune Suppression in Peripheral Blood Mononuclear Cells.

OBJECTIVES: We hypothesized that the immunosuppressive effects associated with antibiotics, sedative...

Detection of Patients at Risk of Multidrug-Resistant Enterobacteriaceae Infection Using Graph Neural Networks: A Retrospective Study.

: While Enterobacteriaceae bacteria are commonly found in the healthy human gut, their colonization ...

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